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Google's AlphaGo Will Face Its Biggest Challenge Yet Next Month -- But Why Is It Still Playing? (theguardian.com)
From a report on The Guardian: A year on from its victory over Go star Lee Sedol, Google DeepMind is preparing a "festival" of exhibition matches for its board game-playing AI, AlphaGo, to see how far it has evolved in the last 12 months. Headlining the event will be a one-on-one match against the current number one player of the ancient Asian game, 19-year-old Chinese professional Ke Jie. DeepMind has had its eye on this match since even before AlphaGo beat Lee. On the eve of his trip to Seoul in March 2016, the company's co-founder, Demis Hassabis, told the Guardian: "There's a young kid in China who's very, very strong, who might want to play us." As well as the one-on-one match with Jie, which will be played over the course of three games, AlphaGo will take part in two other games with slightly odder formats. But why is Google's AI still playing Go, you ask? An article on The Outline adds: Its [Google's] experiments with Go -- a game thought to be years away from being conquered by AI before last year -- are designed to bring us closer to designing a computer with human-like understanding that can solve problems like a human mind can. Historically, there have been tasks that humans do well -- communicating, improvising, emoting -- and tasks that computers do well, which tend to be those that require lots of computations -- like math of any kind, including statistical analysis and modeling of, say, journeying to the moon. Slowly, artificial intelligence scientists have been pushing that barrier. [...] Go is played on a board with an 19-by-19 grid (updated after readers pointed out it's not 18x18 grid). Each player takes turn placing stones (one player with white, the other with black) on empty intersections of the grid. The goal is to completely surround the stones of another player, removing them from the board. The number of possible positions compared to chess thanks in part to the size of the board and ability to take any unoccupied position is part of what makes it so complex. As DeepMind co-founder Demis Hassabis put it last year, "There are 1,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,
000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,
000,000,000,000,000,000,000,000,000,000 possible positions."
number of possible positions as reported by Demis Hassabis.
If you've read any of the professional commentary on the play style of AlphaGo, it's nothing like a human. The crux of it's ability is to be able to calculate the status of the board to the fraction of a point and take moves that advance the position by fractions of a point. Humans on the other hand tend to make moves that will swing the board by several points. As a result Alphago will never play a kami no itte, unlike Sedol who did in his single win against the computer. In other words, AlphaGo is better at microagression and the humans are still better at "the perfect play". Unfortunately for humans, it takes the absolute perfect play to beat microagression.